A Review of Control Techniques for Wind Energy Conversion System

Wind energy is the most efficient and advanced form of renewable energy (RE) in recent decades, and an effective controller is required to regulate the power generated by wind energy. This study provides an overview of state-of-the-art control strategies for wind energy conversion systems (WECS). Studies on the pitch angle controller, the maximum power point tracking (MPPT) controller, the machine side controller (MSC), and the grid side controller (GSC) are reviewed and discussed. Related works are analyzed, including evolution, software used, input and output parameters, specifications, merits, and limitations of different control techniques. The analysis shows that better performance can be obtained by the adaptive and soft-computing based pitch angle controller and MPPT controller, the field-oriented control for MSC, and the voltage-oriented control for GSC. This study provides an appropriate benchmark for further wind energy research

Intelligent flight control systems

The capabilities of flight control systems can be enhanced by designing them to emulate functions of natural intelligence. Intelligent control functions fall in three categories. Declarative actions involve decision-making, providing models for system monitoring, goal planning, and system/scenario identification. Procedural actions concern skilled behavior and have parallels in guidance, navigation, and adaptation. Reflexive actions are spontaneous, inner-loop responses for control and estimation. Intelligent flight control systems learn knowledge of the aircraft and its mission and adapt to changes in the flight environment. Cognitive models form an efficient basis for integrating 'outer-loop/inner-loop' control functions and for developing robust parallel-processing algorithms

Performance and Configuration Analysis of Tracking Time Anti-Windup PID Controllers

As popular as the application of Proportional Integral Derivative (PID) controller is, issues relating to saturation effects are still being addressed using different techniques.  Amongst such techniques are clamping anti-windup technique and back-calculation anti-windup techniques which primary prevent the integral term of the PID control action from reaching saturation. Separate tracking time technique was applied to both cases of anti-windup techniques investigated in this research unlike the conventional tracking time.  These anti-windup controllers were used to control the operation of a motorized globe valve.  The results obtained after simulation in MATLAB Simulink environment showed that both techniques gave similar outputs with a stable response of magnitude 0.95 at 1.5 seconds settling time when a unit step reference input signal was applied as compared to conventional PID controller that had an overshoot of 1.04 before settling to a magnitude of 1.0 at 1.5 seconds. Vibration, instability, and operational distortion were experienced when the anti-windup techniques were cascaded.  The same responses were obtained when their outputs were combined to control the motorized globe valve.  Other interesting mathematical models of important components are contained in the full paper

Modeling and control of hard disk drive in mobile applications

Master'sMASTER OF ENGINEERIN

Application of Sliding Mode Controller and Linear Active Disturbance Rejection Controller to a PMSM Speed System

Permanent magnet synchronous motor (PMSM) is a popular electric machine in industry for its small volume, high electromagnetic torque, high reliability and low cost. It is broadly used in automobiles and aircrafts. However, PMSM has its inherent problems of nonlinearity and coupling, which are challenges for control systems design. In addition, the external disturbances such as load variation and noises could degrade the systems performance. Both sliding mode control (SMC) and active disturbance rejection control (ADRC) are robust against disturbances. They can also compensate the nonlinearity and couplings of the PMSM. Therefore, in this thesis, we apply both SMC and ADRC to a PMSM speed system. Our control goal is to drive the speed outputs of the PMSM speed system to reference signals in the presences of nonlinearity, disturbance, and parameter variations. Simulation results verify the effectiveness of SMC and ADRC on the speed control for PMSM systems in spite of the presences of external disturbance and internal system uncertaintie

Intelligent methods for complex systems control engineering

This thesis proposes an intelligent multiple-controller framework for complex systems that incorporates a fuzzy logic based switching and tuning supervisor along with a neural network based generalized learning model (GLM). The framework is designed for adaptive control of both Single-Input Single-Output (SISO) and Multi-Input Multi-Output (MIMO) complex systems. The proposed methodology provides the designer with an automated choice of using either: a conventional Proportional-Integral-Derivative (PID) controller, or a PID structure based (simultaneous) Pole and Zero Placement controller. The switching decisions between the two nonlinear fixed structure controllers is made on the basis of the required performance measure using the fuzzy logic based supervisor operating at the highest level of the system. The fuzzy supervisor is also employed to tune the parameters of the multiple-controller online in order to achieve the desired system performance. The GLM for modelling complex systems assumes that the plant is represented by an equivalent model consisting of a linear time-varying sub-model plus a learning nonlinear sub-model based on Radial Basis Function (RBF) neural network. The proposed control design brings together the dominant advantages of PID controllers (such as simplicity in structure and implementation) and the desirable attributes of Pole and Zero Placement controllers (such as stable set-point tracking and ease of parameters’ tuning). Simulation experiments using real-world nonlinear SISO and MIMO plant models, including realistic nonlinear vehicle models, demonstrate the effectiveness of the intelligent multiple-controller with respect to tracking set-point changes, achieve desired speed of response, prevent system output overshooting and maintain minimum variance input and output signals, whilst penalising excessive control actions

Advanced control designs for output tracking of hydrostatic transmissions

The work addresses simple but efficient model descriptions in a combination with advanced control and estimation approaches to achieve an accurate tracking of the desired trajectories. The proposed control designs are capable of fully exploiting the wide operation range of HSTs within the system configuration limits. A new trajectory planning scheme for the output tracking that uses both the primary and secondary control inputs was developed. Simple models or even purely data-driven models are envisaged and deployed to develop several advanced control approaches for HST systems

U-model based adaptive internal model control for tracking of nonlinear dynamic plants

We present a technique to infer lower bounds on the worst-case runtime complexity of integer programs, where in contrast to earlier work, our approach is not restricted to tail-recursion. Our technique constructs symbolic representations of program executions using a framework for iterative, under-approximating program simplification. The core of this simplification is a method for (under-approximating) program acceleration based on recurrence solving and a variation of ranking functions. Afterwards, we deduce asymptotic lower bounds from the resulting simplified programs using a special-purpose calculus and an SMT encoding. We implemented our technique in our tool LoAT and show that it infers non-trivial lower bounds for a large class of examples